ph-audio-classification-v1
This model is a fine-tuned version of ntu-spml/distilhubert on the audiofolder dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.3404
- eval_accuracy: 1.0
- eval_runtime: 0.8233
- eval_samples_per_second: 8.503
- eval_steps_per_second: 1.215
- epoch: 1.0
- step: 4
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for herbiel/ph-audio-classification-v1
Base model
ntu-spml/distilhubert